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92 CHAPTER 5. BENCHMARKING OF EVENT-BASED SYSTEMS<br />

No. Msg.<br />

9000<br />

8000<br />

7000<br />

6000<br />

5000<br />

4000<br />

3000<br />

2000<br />

1000<br />

0<br />

40 80 120 160 200 240 280<br />

Base<br />

a<br />

b<br />

c<br />

d<br />

Kbytes<br />

20000<br />

18000<br />

16000<br />

14000<br />

12000<br />

10000<br />

8000<br />

6000<br />

4000<br />

2000<br />

0<br />

40 80 120 160 200 240 280<br />

Base<br />

a<br />

b<br />

c<br />

d<br />

Figure 5.9: Horizontal Topology: # msg.<br />

sent<br />

Figure 5.10: Message Traffic in Kbytes<br />

type <strong>and</strong> the b<strong>and</strong>width they use are scaled as a function <strong>of</strong> the BASE parameter. As evident<br />

from the figure, when scaling the workload the proportions <strong>of</strong> the different types <strong>of</strong> messages<br />

remain constant. This is expected since the relative weights <strong>of</strong> the various messaging styles used<br />

by the workload should not depend on the scaling factor.<br />

The sizes <strong>of</strong> the messages used in the various interactions have been chosen to reflect typical<br />

message sizes in real-life MOM applications. Pub/sub messages are generally much smaller<br />

than P2P messages due to the decoupled nature <strong>of</strong> the delivery mechanism. For every type<br />

<strong>of</strong> message, SPECjms2007 generates messages with sizes chosen from a discrete distribution<br />

with three possible values as shown in Table 5.5. There are two exceptions, the priceUpdate<br />

message used in Interaction 4 <strong>and</strong> the statInfoSM message used in Interaction 5. The former<br />

has a fixed size, while the latter has size between 4.7 <strong>and</strong> 24.78 KBytes with an average <strong>of</strong><br />

5.27 KBytes. Since statInfoSM messages contain sales statistics, their size is determined by<br />

the rate at which items are sold in supermarkets which depends on the number <strong>of</strong> customers<br />

visiting a supermarket per day <strong>and</strong> the average number <strong>of</strong> items sold per customer.<br />

P2P transactional messages tend to be medium in size <strong>and</strong> P2P non-transactional range from<br />

very small (≤ 1KBytes) to big (50 KBytes). Large messages are very rarely used in practice.<br />

We decided to model three different messages sizes per message type based on a certain<br />

probability:<br />

• Small messages: up to 2 KBytes, probability 95 %<br />

• Medium messages: up to 10 KBytes, probability <strong>of</strong> 4 %<br />

• Large messages: up to 55 KBytes, probability <strong>of</strong> 1 %<br />

Vertical Topology<br />

The goal <strong>of</strong> the vertical topology is to exercise the ability <strong>of</strong> the system to h<strong>and</strong>le increasing<br />

message traffic through a fixed set <strong>of</strong> destinations. Therefore, a fixed set <strong>of</strong> physical locations<br />

is used <strong>and</strong> the workload is scaled by increasing the rate at which interactions are executed.<br />

Similar to the horizontal case, a single parameter BASE is used as a scaling factor. The following<br />

rules are enforced:<br />

1. |Ψ SM | = 10<br />

2. |Ψ DC | = 2<br />

3. |Ψ SP | = 5

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